Every experiment found that as you increase productivy it decreases diversity, which doesn't follow the natural productivity/species-richness curve (this is gaining interest in the community: we are increasing productivity of systems in general with environmental change going on, e.g., urbanization increases nitrogen/fertizilation, and a desire to know the result on diversity)

What is Primary Productivity "can of worms" discussion

Want to aggregate data at many different scales/communities to get many types of graphs; you want to ultimately go from smallest possible scale to largest scale (infer curve of graph)

What decision making occurs before any analysis happens? This goes into the data discovery/integration. Deana: can we build a repository of methodologies?

You do a broad category of the dataset, but not the details (a little bit of woody stuff, and so on...)

Bob: need a step where someone can look at the methodology ...

Rich: Need to capture what it is you are measuring; it isn't as much a methodology issue

Bob: Clark and Clark paper covers some of this (Bob said he'd dig up the ref)

Most of the time, productivity scales well, i.e., it is a linear scaling, e.g., anpp vs. area is a linear relationship. So for example, even though they are smaller plots, you can get g/m^2 measures. Basically, productivity doubles as area doubles...

N addition decreases species diversity: plot at lter sites of anpp (above-ground primary productivity) versus relative species density; species density is the number of species observed in a given area

Two studies, measures at different scales: either you simulate or measure a species area curve, and extrapolate to different areas.

Both projects pretty much took from the same original, "raw" data sets

34 from Katy's project

13 sites from NCEAS project

Brainstorming:

Six-month view: we know diversity made up of species, we have all that data, but don't use it to its full potential, productivity/diversity data needs to be integrated with community structure, and integrating across a lot of sites.

General tasks: Identifying data that is relevant (talking with people), permission to obtain the data, understanding the structure and content of the data (sampling design, how or what attributes mean), and then determining which can be appropriately integrated to do an analysis. From Jornada: http://jornada-www.nmsu.edu/ (go to "Research Data" > "LTER Data" > "Plant")

anpp versus r and a bunch of data points. how can the data points be linked back to a table of other features ... of the species that are involved in the point. The point represents the set of species in an area (the species "richness") ... the auxiliary table is characteristics of the species

As another example, compare what happens to the species between the points (as area increases); and more importantly the functional traits of the change

The discussion broadly covered traits of plant communities important in biodiversity and productivity experiments and experimental methodologies. The following notes are raw and will require considerable work to formalize. As such, the categorizations suggested by the indented formatting should be regarded as preliminary.

Traits of a Population (aggregated group of individuals) of Plant Species:

Abundance

Count

Cover

Biomass

Size

Height

Mean, variance of “average height of the highest photosynthetic organ of a well-grown individual”

Biomass

Avg above ground biomass of an individual

Avg Canopy size (area)

Path of Resource Uptake

Photosynthesis (C3, C4, CAM)

Nitrogen fixing

Microrhyzal fungi associations (Yes/no, Endo/ecto)

Modes of Reproduction

Clonality (None/clumping/branching).

What is the definition used to separate clumping and branching?

Resprouting ability

Life Form/Habit

Grass

Forb

Subshrub

Shrub

Tree

Vine

All these may be definable using other traits (height, woodiness, leaf shape, self-supportingness, perhaps others.

Life Span

Annual, biennial, perennial

Phenological Traits

Seasonality

Sprouting cue

Native/naturalized/non-native

Traits of Parts of Plants: (note the important plant parts given by the trait categories)

Given an annotated schema S, denoted S*. And a white-box actor q s.t. q(S*) -> S’. We want to “push through” the annotations to obtain S’*.

The “nested” transpose is basically a combination of various lower-level algebraic operators, such as (theoretical) group-by, matrix transpose, projection, etc. So, given q as such a plan of operators, can we reason over the plan (white box-actor) q to obtain S*’? Using symbolic manipulation? Using the chase, e.g., for similar problems in integrity constraints?

Often-found pattern of computation

Can Kepler/Ptolemy efficiently and conveniently support the following pattern?

Given a data set, construct a scatter plot for pairs of variables, allow user to select a subset of the plots -or- pairs of variables of interest, return data subsets based on chosen pairs (with no extraneous variables)

Similarly, given data sets, an actor computes a set of regressions, the user is shown the results, the user selects the regressions of interest, and the workflow then proceeds using only those selected regressions

These "patterns" can be supported now (with lots of plumbing) using the browser actor. Can we also add functionality to better support/model these patterns?

This material is based upon work supported by the National Science
Foundation under award 0225676. Any opinions, findings and conclusions or
recomendations expressed in this material are those of the author(s) and do
not necessarily reflect the views of the National Science Foundation (NSF).